The present invention relates to a method for controlling a harvesting machine, in particular a self-propelled harvesting machine such as a combine harvester, a forage harvester, etc., with which various units of the harvesting machine are adjusted and/or monitored in a plurality of separate, defined control processes based on certain received control commands.
The present invention further relates to a corresponding control unit with which a control method of this type can be carried out, and a harvesting machine with a control unit of this type.
Agricultural harvesting machines include one or more adjustable working units for processing various crop materials. With modern harvesting machines, the individual units are equipped with adjusting devices—which are usually remotely controllable from the driver's cab—with which various control parameters of the working units can be set. Typical working units of a combine harvester are, e.g., the threshing mechanism, which usually includes a concave and one or more cylinders, and a cleaning unit located downstream of the threshing mechanism, the cleaning unit typically including a blower and a plurality of sieves. In addition, every self-propelled harvesting machine includes a related working unit that drives the harvesting machine. Different types of crops and harvesting conditions, such as moisture, crop height, ground conditions, etc., require that the individual units and/or their adjustable control parameters be adjusted as exactly as possible to the specific, on-going harvesting process, in order to obtain an optimum overall operating result.
Despite the many setting aids offered to operators by the manufacturers of harvesting machines—such as comprehensive operator training, printed lists of setting values predetermined for various harvesting situations that the operator can refer to, and electronic tools such as electronic fieldwork information systems preprogrammed with optimized combinations of setting values for highly diverse harvesting situations for the operator to choose from—it is still relatively difficult for operators to adjust the machine such that it functions in an optimum manner in accordance with the desired requirements. This is the case, in particular, for inexperienced and/or untrained operators, particularly at the beginning of a harvesting season. In many cases, therefore, the harvesting machine and/or its working units are not adapted to the current harvesting process in an optimum manner. As a result, the available harvesting capacity of the machine is under-utilized, poor operating results are obtained, or, in some cases, unnecessary crop losses result.
To solve this problem, a growing number of processes for adjusting—and optimizing, in particular—and/or monitoring the harvesting machine and/or its units are being automated. For example, DE 101 47 733 A1 describes an automated method for optimizing the threshing mechanism and cleaning unit of an agricultural harvesting machine. With this method, only one control parameter of the harvesting machine is varied, while the setting and harvesting conditions remain the same. Subsequently, by comparing the working results, precisely that setting value is selected for the particular control parameter that yielded a better working result. The operating-result values can be recorded, in particular, and, by referring to the recorded operating results, a relationship between the varied setting parameter and the operating result obtained can be identified, based on which an optimum setting parameter can be selected. Using this method, even inexperienced operators learn relatively quickly whether, when and to what extent the varied control parameter affects the operating result, and they can set the control parameter accordingly. The setting can also be carried out automatically, of course.
Furthermore, a control unit is described in DE 102 53 081 A1 with which the ground speed of a harvesting machine can be automatically set and monitored.
One of the problems associated with the automation of processes of this type is that certain control processes can collide with each other. To optimize the threshing mechanism setting or the cleaning unit, for example, the ground speed must be regulated such that the throughput is constant. Activating a ground speed regulation that regulates with respect to a constant ground speed or loss would not be suitable in this case. In addition, it would be counterproductive if optimization of the threshing mechanism and the cleaning unit would take place simultaneously, since, when the threshing mechanism is adjusted, the input parameters for the cleaning unit are changed, and optimization of the cleaning unit requires at least short-term variations in the threshing mechanism setting.
The greater the number of individual subprocesses that are automated on the harvesting machine, the more difficult it is for the operator to determine which processes are allowed to run simultaneously and, if so, in which operating modes.
Publication EP 1 277 388 A1 describes a control system with a learning fuzzy interference system with fuzzy logic that is capable of learning working conditions and recalling them. This control system is designed to prevent the situation in which interactions between various harvesting subsystems, i.e., between various automated subprocesses, for controlling various units of the harvesting machine are not taken into consideration, which would result in erroneous adjustments. The control system described in that publication is extremely complicated in design and requires a considerable amount of computing capacity and computing speed, neither of which is available in harvesting machines at this time.